Earn a scholarship from Facebook and Udacity, and learn how to build, train, and deploy state-of-the-art deep learning models with PyTorch. Apply today!

PyTorch is an open source deep learning framework that’s quickly become popular with AI researchers for its ease of use, clean Pythonic API, and flexibility. With the preview release of PyTorch 1.0, developers can now seamlessly move from exploration to production deployment using a single, unified framework.

Facebook’s support and investment will make 10,000 seats available for a new Udacity Challenge Course; “Introduction to Deep Learning with PyTorch.” Upon successfully completing the first phase of the program, 300 students will then go on to earn full scholarships.

New Course: Introduction to Deep Learning with PyTorch

We’re thrilled to have Soumith Chintala contributing to the new Intro to Deep Learning with PyTorch course. Not only is Soumith an Artificial Intelligence Research Engineer at Facebook, he is the creator of PyTorch. His invaluable contributions in our classroom make this a truly singular learning experience for anyone interested in advancing their deep learning and AI skills. In the course, students will gain expertise with the basics of deep learning, and build their own deep neural networks using PyTorch. They’ll also get practical experience with PyTorch through coding exercises and projects implementing state-of-the-art AI applications such as style transfer and text generation.

“As an AI professional and practitioner, I personally love using PyTorch, because it fits perfectly into a normal Python data workflow, it’s easy to build both simple and complex networks, and now with the new features you can easily deploy your models. I’m extremely excited to support our students as they master this tool, and start to apply it in their own new and innovative ways.” —Mat Leonard, Product Lead, Udacity School of AI

The PyTorch Scholarship Challenge from Facebook

The PyTorch Scholarship Challenge from Facebook is structured in two phases:

Phase 1 is the Challenge Course. The duration of this course is two months, and program participants will receive support from community managers throughout their learning experience, as they become part of a dynamic student community and network of scholars.

In Phase 2, the top 300 students (in terms of output and collaboration) from the first phase will earn full scholarships to Udacity’s Deep Learning Nanodegree program, where they’ll cover topics such as: Convolutional and Recurrent Neural Networks, Generative Adversarial Networks, Deployment, and more. Students will use PyTorch, and have access to GPUs to train models faster, as they learn from authorities like Sebastian Thrun, Ian Goodfellow, Jun-Yan Zhu, and Andrew Trask.

Expanded Partnership: Facebook and Udacity

This new offering is an exciting expansion of a partnership that launched with Mobile Developer Education at F8 in April 2017, followed by the launch of our new Mobile Design and Usability course in November 2017.

Now, with the addition of Intro to Deep Learning with PyTorch to the Udacity-Facebook catalogue—and the creation of the new PyTorch Scholarship Challenge from Facebook—both organizations can look forward to a fantastic influx of new learners focused on mastering the boldest and most important AI and deep learning tools.

We’re thrilled to collaborate with Facebook in creating incredible learning experiences for deserving students across the globe, and Facebook’s commitment to supporting the next generation of AI talent is something we’re excited to match lesson for lesson, program for program, and opportunity for opportunity.

Stuart Frye

Stuart Frye is Vice President of Business Development at Udacity, overseeing all of Udacity's strategic partnerships, government, and economic opportunity work. Stuart has over 15 years experience as an education entrepreneur and considers education to be the single most powerful lever our students have to create better life opportunities.
Prior to Udacity, Stuart was CEO and co-founder of Eduvant, providing data analytics for K12 districts and charter schools. He started his career in education opening schools across China with Aston Educational Group. He also led case teams as a strategy consultant with the Monitor Group. Stuart is based in San Francisco and has lived and worked in Boston as well as China.

Thank you for your questions, and first off, congratulations on earning your Deep Learning Nanodegree program credential! Regarding this specific experience, you are more than welcome to enroll in the new PyTorch course; it’s free, and the curriculum is excellent. But, given that the scholarship award is enrollment in the program you’ve already graduated from, you might then next want to consider exploring some of the more advanced options in our School of AI, such as Computer Vision or Natural Language Processing.

The opportunity is open to anyone eager to expand their deep learning and AI skills (who is at least 18 years of age, and who possesses intermediate Python knowledge). Applicants should be prepared to commit approximately 10 hours of study per week during the Challenge Course phase. Should you earn a scholarship to the Deep Learning Nanodegree program, you should expect to maintain that same level of commitment. So, put another way, yes!

Thank you for your question, and for your interest in this offering. Unfortunately, relevant law from the U.S. Treasury Department currently prevents this. We are hopeful that this situation will change in the future.

I finished Udacity deep learning nanodegree but was not even selected for pytorch course. Very disappointing and in the future I will not take any other nanodegree courses. Apparently finishing it doesn’t even made me ready for the pytorch course 🙁 so thanks and bye, Udacity

We’re very sorry to hear of your disappointment. There are many factors that go into the selection process, and while command of the material is certainly a key factor, there are other matters as well. We hope you’ll reconsider, and apply for new opportunities as they emerge; we’ve had many, many students earn scholarships on second opportunities, and we’d welcome the opportunity to have you in our classrooms again as well!

I just want to know the difference of this challenge with taking the “intro to Deep Learning with Pytorch” course. I found this course open for free and enroll and going with the lessons without being accepted in this challenge. or I don’t know! We need some clarifications.

Thank you for your question. The key difference is that, in taking the course via the challenge, you enter yourself into the opportunity to earn a full scholarship from Udacity and Facebook, for Udacity’s Deep Learning Nanodegree program. Whereas if you just enroll in the “standard” free course, you don’t have that opportunity. So your decision as to which way to enroll should depend on whether you want to try and earn the scholarship opportunity. Hope that’s clear, but please let us know if you have additional questions, thank you!